To dynamically update the shape of orebody according to the knowledge of a structural geologist’s insight,an approach of orebody implicit modeling from raw drillhole data using the generalized radial basis function i...To dynamically update the shape of orebody according to the knowledge of a structural geologist’s insight,an approach of orebody implicit modeling from raw drillhole data using the generalized radial basis function interpolant was presented.A variety of constraint rules,including geology trend line,geology constraint line,geology trend surface,geology constraint surface and anisotropy,which can be converted into interpolation constraints,were developed to dynamically control the geology trends.Combined with the interactive tools of constraint rules,this method can avoid the shortcomings of the explicit modeling method based on the contour stitching,such as poor model quality,and is difficult to update dynamically,and simplify the modeling process of orebody.The results of numerical experiments show that the 3D ore body model can be reconstructed quickly,accurately and dynamically by the implicit modeling method.展开更多
Quantum key distribution(QKD)is a technology that can resist the threat of quantum computers to existing conventional cryptographic protocols.However,due to the stringent requirements of the quantum key generation env...Quantum key distribution(QKD)is a technology that can resist the threat of quantum computers to existing conventional cryptographic protocols.However,due to the stringent requirements of the quantum key generation environment,the generated quantum keys are considered valuable,and the slow key generation rate conflicts with the high-speed data transmission in traditional optical networks.In this paper,for the QKD network with a trusted relay,which is mainly based on point-to-point quantum keys and has complex changes in network resources,we aim to allocate resources reasonably for data packet distribution.Firstly,we formulate a linear programming constraint model for the key resource allocation(KRA)problem based on the time-slot scheduling.Secondly,we propose a new scheduling scheme based on the graded key security requirements(GKSR)and a new micro-log key storage algorithm for effective storage and management of key resources.Finally,we propose a key resource consumption(KRC)routing optimization algorithm to properly allocate time slots,routes,and key resources.Simulation results show that the proposed scheme significantly improves the key distribution success rate and key resource utilization rate,among others.展开更多
As mining operations extend to greater depths, the risk of deformation in high-stress tunnels increases significantly, posing a substan-tial threat. This study introduces a novel framework known as“robust mobility de...As mining operations extend to greater depths, the risk of deformation in high-stress tunnels increases significantly, posing a substan-tial threat. This study introduces a novel framework known as“robust mobility deformation detection” (RM2D), designed for real-timetunnel deformation detection. RM2D employs mobile LiDAR scanner to capture real-time point cloud data within the tunnel. This datais then voxelized and analyzed using covariance matrices to create a voxel-based multi-distribution representation of the rugged tunnelsurface. Leveraging this representation, we assess deformations and scrutinize results through machine learning models to swiftly pin-point tunnel deformation locations. Extensive experimental validation confirms the framework’s capacity to successfully detect deforma-tions, including floor heave, side rib spalling, and roof fall, with remarkable accuracy. For deformation levels at 0.15 m, RM2D was ableto successfully detect deformations with an area greater than 2 m^(2) . For deformation areas of (3 ± 0.5) m^(2) , RM2D successfully detecteddeformations of levels at (0.05 ± 0.01) m, and its detection capability meets the standard criteria for mining tunnel deformation detec-tion. When compared to two conventional methods, RM2D demonstrates its real-time deformation detection capability in complex envi-ronments and on rough surfaces with precision, all at speeds below 10 km/h. Furthermore, we evaluated the predictive performance usingmultiple evaluation metrics and provided insights into the decision mechanism of the machine learning employed in our research, therebyoffering valuable information for practical engineering applications in tunnel deformation detection.展开更多
The reentry vehicle will encounter thermal ablation,especially at the stagnation point regime.A theoretical work has been done to analyze the thermal effect of gas blowing due to thermal ablation of surface material o...The reentry vehicle will encounter thermal ablation,especially at the stagnation point regime.A theoretical work has been done to analyze the thermal effect of gas blowing due to thermal ablation of surface material on the head of a general hypersonic vehicle.By deriving the formulation,research takes into account the effect of gas blowing on the thermal dynamics balance,and then solves them by numerical discretization.It is found that gas blowing will increase the temperature and heat flux at the surface of stagnation point regime.展开更多
文摘To dynamically update the shape of orebody according to the knowledge of a structural geologist’s insight,an approach of orebody implicit modeling from raw drillhole data using the generalized radial basis function interpolant was presented.A variety of constraint rules,including geology trend line,geology constraint line,geology trend surface,geology constraint surface and anisotropy,which can be converted into interpolation constraints,were developed to dynamically control the geology trends.Combined with the interactive tools of constraint rules,this method can avoid the shortcomings of the explicit modeling method based on the contour stitching,such as poor model quality,and is difficult to update dynamically,and simplify the modeling process of orebody.The results of numerical experiments show that the 3D ore body model can be reconstructed quickly,accurately and dynamically by the implicit modeling method.
基金Project supported by the Natural Science Foundation of Jilin Province of China(Grant No.20210101417JC).
文摘Quantum key distribution(QKD)is a technology that can resist the threat of quantum computers to existing conventional cryptographic protocols.However,due to the stringent requirements of the quantum key generation environment,the generated quantum keys are considered valuable,and the slow key generation rate conflicts with the high-speed data transmission in traditional optical networks.In this paper,for the QKD network with a trusted relay,which is mainly based on point-to-point quantum keys and has complex changes in network resources,we aim to allocate resources reasonably for data packet distribution.Firstly,we formulate a linear programming constraint model for the key resource allocation(KRA)problem based on the time-slot scheduling.Secondly,we propose a new scheduling scheme based on the graded key security requirements(GKSR)and a new micro-log key storage algorithm for effective storage and management of key resources.Finally,we propose a key resource consumption(KRC)routing optimization algorithm to properly allocate time slots,routes,and key resources.Simulation results show that the proposed scheme significantly improves the key distribution success rate and key resource utilization rate,among others.
基金supported in part by the National Key Research and Development Program of China(Grant No.2023YFC2907305).
文摘As mining operations extend to greater depths, the risk of deformation in high-stress tunnels increases significantly, posing a substan-tial threat. This study introduces a novel framework known as“robust mobility deformation detection” (RM2D), designed for real-timetunnel deformation detection. RM2D employs mobile LiDAR scanner to capture real-time point cloud data within the tunnel. This datais then voxelized and analyzed using covariance matrices to create a voxel-based multi-distribution representation of the rugged tunnelsurface. Leveraging this representation, we assess deformations and scrutinize results through machine learning models to swiftly pin-point tunnel deformation locations. Extensive experimental validation confirms the framework’s capacity to successfully detect deforma-tions, including floor heave, side rib spalling, and roof fall, with remarkable accuracy. For deformation levels at 0.15 m, RM2D was ableto successfully detect deformations with an area greater than 2 m^(2) . For deformation areas of (3 ± 0.5) m^(2) , RM2D successfully detecteddeformations of levels at (0.05 ± 0.01) m, and its detection capability meets the standard criteria for mining tunnel deformation detec-tion. When compared to two conventional methods, RM2D demonstrates its real-time deformation detection capability in complex envi-ronments and on rough surfaces with precision, all at speeds below 10 km/h. Furthermore, we evaluated the predictive performance usingmultiple evaluation metrics and provided insights into the decision mechanism of the machine learning employed in our research, therebyoffering valuable information for practical engineering applications in tunnel deformation detection.
基金National Key Research and Development Plan of China through the project No.2019YFA0405200.
文摘The reentry vehicle will encounter thermal ablation,especially at the stagnation point regime.A theoretical work has been done to analyze the thermal effect of gas blowing due to thermal ablation of surface material on the head of a general hypersonic vehicle.By deriving the formulation,research takes into account the effect of gas blowing on the thermal dynamics balance,and then solves them by numerical discretization.It is found that gas blowing will increase the temperature and heat flux at the surface of stagnation point regime.
